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This lecture by the instructor Mackenzie Mathis explores the use of mice and machine learning to understand cortical contributions to forelimb motor adaptation. The Center for Intelligent Systems (CIS) at EPFL aims to advance research in intelligent systems. The lecture covers topics such as neural circuits, motor control, adaptive behavior, and reverse engineering adaptive motor control. It delves into the study of motor learning in the lab, force-field adaptation paradigms, and proposed learning mechanisms for motor adaptation. The role of the somatosensory cortex in forelimb motor adaptation in mice is discussed, along with the use of DeepLabCut for animal pose estimation and task-driven neural network models for proprioception.